A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context

Majid Azadi, Mostafa Jafarian, Reza Farzipoor Saen*, Seyed Mostafa Mirhedayatian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

266 Citations (Scopus)

Abstract

Sustainable supply chain management (SSCM) has received much consideration from corporate and academic over the past decade. Sustainable supplier performance evaluation and selection plays a significant role in establishing an effective SSCM. One of the techniques that can be used for sustainable supplier performance evaluation and selection is data envelopment analysis (DEA). In real world problems, the inputs and outputs might be imprecise. This paper develops an integrated DEA enhanced Russell measure (ERM) model in fuzzy context to select the best sustainable suppliers. A case study is presented to exhibit the efficacy of the proposed method for sustainable supplier selection problem in a resin production company. The case study demonstrates that the proposed model can measure effectiveness, efficiency, and productivity in uncertain environment with different α levels. Also, it shows that the proposed model aids decision makers to deal with economic, social, and environmental factors when selecting sustainable suppliers.

Original languageEnglish
Pages (from-to)274-285
Number of pages12
JournalComputers and Operations Research
Volume54
DOIs
Publication statusPublished - Feb 2015

Keywords

  • Data envelopment analysis
  • Fuzzy productivity value
  • Integrated enhanced russell measure (ERM) model
  • Sustainable supplier selection
  • Sustainable supply chain management (SSCM)

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research

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